Project Summary/Abstract A fundamental goal in neuroscience is to understand how information is processed in neuronal circuits. Ultimately, we would like to understand the relationship between circuit structure and network function. However, the immense complexity of most brain networks has been a significant barrier to progress. Neurons are a primary computational component of networks in the brain, yet we do not have a comprehensive list of their types for even the simplest mammalian neuronal circuit. Moreover, a neuron?s function is fundamentally dependent on how it is connected within its network, yet mammalian neuronal networks consist of billions of cells with trillions of connections. How can we get a handle on such a complex computational machine? Recent advances in large-scale electron microscopy (EM) and molecular genetic tools have allowed us to begin detailed mapping of neural network anatomy and cellular physiology. The cerebellum is an excellent system to validate our novel platform as part of a systematic effort to reverse engineer a functional neural circuit that is involved in motor control and social behavior. Its basic structure is well ordered, relatively simple and sufficiently described to have inspired computational models that capture aspects of cerebellar function. However, even the most advanced models are limited by an incomplete characterization of the cell types and connectivity within the cerebellum. Here, we propose to validate our next-generation large-scale EM platform and provide a comprehensive characterization of cerebellar circuitry. We will use tools recently developed in our lab to a circuit that offers the advantages of relative simplicity and a strong starting foundation. These studies will allow us to understand principles of cerebellar circuit organization and may help us determine the role of specific circuit elements in neurodegenerative disorders.